利用d肽靶向SARS-CoV-2受体结合域和主要蛋白酶

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Laiyi Feng,Jingjia Liu,Chunmei Li,Qian Wang,Luhua Lai,Changsheng Zhang
{"title":"利用d肽靶向SARS-CoV-2受体结合域和主要蛋白酶","authors":"Laiyi Feng,Jingjia Liu,Chunmei Li,Qian Wang,Luhua Lai,Changsheng Zhang","doi":"10.1021/acs.jcim.5c01839","DOIUrl":null,"url":null,"abstract":"D-peptide binders are promising drug candidates that may offer better binding specificity and improved metabolic stability than canonical peptide drugs. However, there is a lack of efficient computational methods for the de novo design of D-peptide binders based on target protein structure. We developed a general framework for de novo design of D-helical peptide binders for the target protein, which consists of curved helical scaffold generation, scaffold docking to the target surface, Rosetta based sequence design, and in silico selection. For the convenience of conformation sampling, the targeted protein is mirrored to D-type, while the peptide ligands are presented in L-type during the sequence design step. We have applied this workflow to design D-helical peptides targeting the two major targets for inhibiting SARS-CoV-2, the receptor binding domain (RBD) of the spike protein and the main protease (3CLpro), to alter its oligomeric state and inhibit its activity. We found that both the receptor binding surface of RBD and the groove between the catalytic and regulation domains of 3CLpro are favorable for the binding of 28-mer D-helical peptides. We designed and tested 8 D-peptides for RBD and found 4 of them bound to RBD with the best one demonstrating submicromolar dissociation constant and the ability to block the binding of full-length spike protein toward its receptor, human angiotensin-converting enzyme 2. For 3CLpro, 3 of the 12 designed D-peptides could inhibit its catalytic activity. And the best peptide LY09 binds 3CLpro with submicromolar dissociation constant and disrupts the dimerization of 3CLpro. The D-peptide binder docking and design tools are publicly available at https://github.com/laiyii/D-peptide-binder-design.","PeriodicalId":44,"journal":{"name":"Journal of Chemical Information and Modeling ","volume":"24 1","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Targeting SARS-CoV-2 Receptor Binding Domain and Main Protease with D-Peptides.\",\"authors\":\"Laiyi Feng,Jingjia Liu,Chunmei Li,Qian Wang,Luhua Lai,Changsheng Zhang\",\"doi\":\"10.1021/acs.jcim.5c01839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"D-peptide binders are promising drug candidates that may offer better binding specificity and improved metabolic stability than canonical peptide drugs. However, there is a lack of efficient computational methods for the de novo design of D-peptide binders based on target protein structure. We developed a general framework for de novo design of D-helical peptide binders for the target protein, which consists of curved helical scaffold generation, scaffold docking to the target surface, Rosetta based sequence design, and in silico selection. For the convenience of conformation sampling, the targeted protein is mirrored to D-type, while the peptide ligands are presented in L-type during the sequence design step. We have applied this workflow to design D-helical peptides targeting the two major targets for inhibiting SARS-CoV-2, the receptor binding domain (RBD) of the spike protein and the main protease (3CLpro), to alter its oligomeric state and inhibit its activity. We found that both the receptor binding surface of RBD and the groove between the catalytic and regulation domains of 3CLpro are favorable for the binding of 28-mer D-helical peptides. We designed and tested 8 D-peptides for RBD and found 4 of them bound to RBD with the best one demonstrating submicromolar dissociation constant and the ability to block the binding of full-length spike protein toward its receptor, human angiotensin-converting enzyme 2. For 3CLpro, 3 of the 12 designed D-peptides could inhibit its catalytic activity. And the best peptide LY09 binds 3CLpro with submicromolar dissociation constant and disrupts the dimerization of 3CLpro. The D-peptide binder docking and design tools are publicly available at https://github.com/laiyii/D-peptide-binder-design.\",\"PeriodicalId\":44,\"journal\":{\"name\":\"Journal of Chemical Information and Modeling \",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2025-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chemical Information and Modeling \",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acs.jcim.5c01839\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Information and Modeling ","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jcim.5c01839","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

摘要

d肽结合物是一种很有前途的候选药物,它可能比标准肽药物提供更好的结合特异性和更好的代谢稳定性。然而,目前缺乏基于靶蛋白结构的d肽结合物从头设计的有效计算方法。我们为目标蛋白的d -螺旋肽结合物的从头设计开发了一个总体框架,包括弯曲螺旋支架的生成、支架与目标表面的对接、基于Rosetta的序列设计和硅选择。为了方便构象取样,在序列设计步骤中将目标蛋白镜像为d型,而肽配体则以l型呈现。我们应用这一工作流程设计了针对抑制SARS-CoV-2的两个主要靶点(刺突蛋白的受体结合域(RBD)和主要蛋白酶(3CLpro))的d -螺旋肽,以改变其寡聚状态并抑制其活性。我们发现RBD的受体结合表面和3CLpro的催化和调节结构域之间的凹槽都有利于28-mer d -螺旋肽的结合。我们设计并测试了8种用于RBD的d -肽,发现其中4种与RBD结合,其中最好的一种具有亚微摩尔解离常数,并且能够阻断全长刺突蛋白与其受体(人血管紧张素转换酶2)的结合。对于3CLpro,设计的12个d肽中有3个可以抑制其催化活性。最佳多肽LY09以亚微摩尔解离常数与3CLpro结合,破坏3CLpro的二聚化反应。d肽结合剂对接和设计工具可在https://github.com/laiyii/D-peptide-binder-design上公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Targeting SARS-CoV-2 Receptor Binding Domain and Main Protease with D-Peptides.
D-peptide binders are promising drug candidates that may offer better binding specificity and improved metabolic stability than canonical peptide drugs. However, there is a lack of efficient computational methods for the de novo design of D-peptide binders based on target protein structure. We developed a general framework for de novo design of D-helical peptide binders for the target protein, which consists of curved helical scaffold generation, scaffold docking to the target surface, Rosetta based sequence design, and in silico selection. For the convenience of conformation sampling, the targeted protein is mirrored to D-type, while the peptide ligands are presented in L-type during the sequence design step. We have applied this workflow to design D-helical peptides targeting the two major targets for inhibiting SARS-CoV-2, the receptor binding domain (RBD) of the spike protein and the main protease (3CLpro), to alter its oligomeric state and inhibit its activity. We found that both the receptor binding surface of RBD and the groove between the catalytic and regulation domains of 3CLpro are favorable for the binding of 28-mer D-helical peptides. We designed and tested 8 D-peptides for RBD and found 4 of them bound to RBD with the best one demonstrating submicromolar dissociation constant and the ability to block the binding of full-length spike protein toward its receptor, human angiotensin-converting enzyme 2. For 3CLpro, 3 of the 12 designed D-peptides could inhibit its catalytic activity. And the best peptide LY09 binds 3CLpro with submicromolar dissociation constant and disrupts the dimerization of 3CLpro. The D-peptide binder docking and design tools are publicly available at https://github.com/laiyii/D-peptide-binder-design.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信